Evidence map›Paper›PMID 33898789›Full record

ArticlePhysics and imaging in radiation oncology2021

Evaluation of image quality of a novel computed tomography metal artifact management technique on an anthropomorphic head and neck phantom.

Daniela Branco, Stephen Kry, Paige Taylor, John Rong, Xiaodong Zhang, Steven Frank, David Followill

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. The accuracy of Eclipse AXB and AAA dose algorithms with dental amalgam.Physical and engineering sciences in medicine · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Daniela BrancoDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
Stephen KryDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
Paige TaylorDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
John RongDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
Xiaodong ZhangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
Steven FrankDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
David FollowillDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 607, Houston, TX 77030, United States.
The University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeArtefacts caused by dental amalgam implants present a common challenge in computed tomography (CT) and therefore treatment planning dose calculations. The goal was to perform a quantitative image quality analysis of our Artifact Management for Proton Planning (AMPP) algorithm which used gantry tilts for managing metal artefacts on Head and Neck (HN) CT scans and major vendors' commercial approaches. MATERIALS AND

methodsMetal artefact reduction (MAR) algorithms were evaluated using an anthropomorphic phantom with a removable jaw for the acquisition of images with and without (baseline) metal artifacts. AMPP made use of two angled CT scans to generate one artifact-reduced image set. The MAR algorithms from four vendors were applied to the images with artefacts and the analysis was performed with respective baselines. Planar HU difference maps and volumetric HU differences were analyzed.

resultsAMPP algorithm outperformed all vendors' commercial approaches in the elimination of artefacts in the oropharyngeal region, showing the lowest percent of pixels outside +- 20 HU criteria, 4%; whereas those in the MAR-corrected images ranged from 26% to 67%. In the region of interest within the affected slices, the commercial MAR algorithms showed inconsistent performance, whereas the AMPP algorithm performed consistently well throughout the phantom's posterior region.

conclusionsA novel MAR algorithm was evaluated and compared to four commercial algorithms using an anthropomorphic phantom. Unanimously, the analysis showed the AMPP algorithm outperformed vendors' commercial approaches, showing the potential to be broadly implemented, improve visualizations in patient anatomy and provide accurate HU information.

Indexed as

AlgorithmAMPP, Artifact Management for Proton PlanningArtifactsComputed X ray tomographyCT, Computed tomographyGantry tiltsHead and neck neoplasmsHU, Hounsfield UnitiMAR, iterative metal artifact reductionkVp, Kilovoltage peakMAR, metal artifact reductionOAR, Organs at RiskOMAR, orthopedic metal artifact reductionSEMAR, single-energy metal artifact reductionSmartMAR, Smart metal artifact reduction

Identifiers

PMID33898789
PMCPMC8058027
OpenAlexW3131071892

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.